We’ve all heard the following retail data urban myth. After mining consumer data, a retailer noticed a significant link in the purchase of diapers and beer. This discovery could have lead to many possible actions (placement of diapers closer to beer for example). While that story may be a myth, the immense power of retail analytics are a definite reality. What are some ways in which retail analytics are transforming the industry today?

1. Customer Sentiment

Facebook has over 800 million users. Twitter has 200 million. Chances are your shoppers are participating in social networks—sharing experiences, positive or negative, and asking for product advice via Facebook, Twitter, Google+, etc. Social analytics can help you sift through the unstructured data on social networks to find the information you need. For example, you can pinpoint a specific complaint that was posted on Twitter on a product and respond appropriately. In addition, if you notice that a potential customer asked his friend on Facebook to suggest a new book to read, you can target that person with a targeted Facebook ad with a special deal for eBooks. Brand preservation to the corporation is a primary concern when leveraging the voice of the customer.

2. Personalization

Every customer is different, from age, education level, martial status and other demographical aspects to their shopping behavior and how they respond to various promotions. While some shoppers respond best to coupons, others may spend more when you give them a free gift with purchase or bonus bucks for a future purchase. By utilizing analytics, you can uncover unique purchasing charactersisticse about each customer, allowing you to personalize your offers, thus ensuring the best possible response rate. Your customers are not necessarily buying less, they are buying differently.

3. Predictability Capability

The predictability capability of retail analytics works in 2 ways. First, analytics are useful for when you are launching a new product that shares a similar profile as an existing product. With analytics, you can predict the type of customers who will purchase the new product by examining info about those who purchased the existing product. Using that information, you can determine the best way to market, position and design deals for the new product.

Analytics can also help you anticipate what you will need in an upcoming event, such as a natural disaster. For the recent Hurricane Irene, predictive analytics showed that before previous storms, customers purchased batteries, Pop Tarts, flashlights, duct tape and other emergency related items. Therefore before Hurricane Irene, retailers could prepare by, reforecasting larger inventory requirements , placing these items on display in the front of the store and provide a discount to customers who purchased a bundle of these goods for the purpose of retaining, rewarding and acquiring new and exiting customers. Predictive inference with real time information against KPI’s with closed loop capabilities will provide the competitive differentiator.

Retail analytics and business intelligence software can provide insight into your customers your products and your processes. By turning these insights from analysis into action, you can provide better, more personalized offerings for your customers, eliciting a higher response, retention and purchase rate.